Resampling Method for Unsupervised Estimation of Cluster Validity
نویسندگان
چکیده
منابع مشابه
Resampling Method for Unsupervised Estimation of Cluster Validity
We introduce a method for validation of results obtained by clustering analysis of data. The method is based on resampling the available data. A figure of merit that measures the stability of clustering solutions against resampling is introduced. Clusters that are stable against resampling give rise to local maxima of this figure of merit. This is presented first for a one-dimensional data set,...
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We introduce a method for validation of results obtained by clustering analysis of data. The method is based on resampling the available data. A gure of merit that measures the stability of clustering solutions against resampling is introduced. Clusters which are stable against resam-pling give rise to local maxima of this gure of merit. This is presented rst for a one-dimensional data set, for...
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Clustering attempts to discover significant groups present in a data set. It is an unsupervised process. It is difficult to define when a clustering result is acceptable. Thus, several clustering validity indices are developed to evaluate the quality of clustering algorithms results. In this paper, we propose to improve the quality of a clustering algorithm called ”CLUSTER” by using a validity ...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2001
ISSN: 0899-7667,1530-888X
DOI: 10.1162/089976601753196030